Video Telemetry Synchronization Using Temporal Indexing
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Solution Overview
Problem
Existing systems cannot efficiently locate specific frames within compressed video sequences associated with a temporal time, making it difficult to synchronize telemetry data with video data for real-time applications, such as aerial reconnaissance, where exact time locations for each video frame cannot be directly acquired due to frame data being compressed and not temporally indexed.
Innovation Solution
A system that parses both telemetry and video data based on temporal information, synchronizing them by using a telemetry data parser that receives Key Length Value formatted data and a video frame extraction module that locates approximate timestamps in compressed data, allowing for interpolation or extrapolation of telemetry data to match video frames, enabling real-time synchronization and rendering of video data on a map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire MPEG transport stream is decoded to locate a specific frame, then the frame can be located with exact temporal accuracy, but the processing time and computational resources required become excessive
Solution Approach 1:
The patent applies preliminary action by extracting and storing temporal index information (presentation time stamps) from the video stream during the encoding phase, before the actual frame location is needed. This pre-extracted temporal data is then used during playback to directly locate frames without decoding the entire stream, thus achieving fast temporal access while maintaining precision.
Solution Approach 2:
The patent extracts the temporal indexing mechanism from the compressed video stream by separating the presentation time stamp metadata from the actual video data. This extraction allows the temporal information to be accessed independently and efficiently, enabling direct frame location without processing the complete encoded stream.
2Quantity of substance
If traditional parsing algorithms are used to process large amounts of streamed data, then data can be parsed, but the system cannot operate in real-time
Solution Approach 1:
The patent segments the data parsing process into distinct phases: initial data extraction, temporal indexing, and synchronized processing. By dividing the parsing workload and using parallel processing for telemetry and video data, the system can handle large data volumes while maintaining real-time performance.
Solution Approach 2:
The patent implements continuous parsing and processing of data streams, where telemetry and video data are processed concurrently and continuously rather than in batches. This continuous operation with overlapping processing stages maintains real-time capability while handling large quantities of streamed data.
3Adaptability or versatility
If telemetry data is acquired at a different rate than video data, then both data types can be collected, but synchronization becomes difficult
Solution Approach 1:
The patent uses feedback mechanisms where the system continuously monitors the timing relationships between telemetry and video data streams. Time stamps from both streams are compared and adjusted, with the system adapting its synchronization process based on observed timing variations to maintain accurate alignment despite different acquisition rates.
Solution Approach 2:
The patent changes the temporal parameters of the data streams by applying time stamp adjustments and interpolation/extrapolation factors. These parameter transformations allow telemetry data acquired at one rate to be precisely aligned with video data at a different rate, maintaining synchronization accuracy while preserving acquisition flexibility.
Data Source
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AI summary
A system is provided that can parse both telemetry data and corresponding encoded video data wherein the telemetry and video data are subsequently synchronized based upon temporal information, such as a time stamp. The telemetry data and the video data are originally unsynchronized and the data for each is acquired by a separate device. The acquiring devices may be located within or attached to an aerial vehicle. The system receives the telemetry data stream or file and the encoded video data stream or file and outputs a series of synchronized video images with telemetry data. Thus, there is telemetry information associated with each video image. The telemetry data may be acquired at a different rate than the video data. As a result, telemetry data may be interpolated or extrapolated to create telemetry data that corresponds to each video image. The present system operates in real¬ time, so that data acquired from aerial vehicles can be displayed on a map.